Since the presence of the d egraded conditions such as illuminative variations, eyelashes or eyelids occlusions,ambiguous outer boundary,etc,the key of recog nition for non-ideal iris in real application is to correctly segment iris region which contains texture features distinguishing a p erson from another.In this paper,we propose the segmentation method for non-ideal iris based on statistical features of images. It consists of three phases,i.e.,inner boundary localization,outer boundary localization,and eyelids detection.In inner bound ary localization,this method localizes pupil and iris center accurately by exploiting Gaussian mixture model (GMM) and multiple string s equilibrium.By GMM,multiple Gaussian distributions are evolved to fit image histogram.For this reason,GMM is adapti ve among iris images in different databases.In outer boundary localization,we present the simplified region-based curve evolution w hich is combined with order statistical filters (OSFs) to guarantee its converge n ce to exterior iris boundary.Finally in eyelids detection we employ parabola to model iris eyelids.By evaluating the databases,this method can segment non-idea l iris accurately by eliminating undesirable reflections and eyelash /eyelid occ lusions.